Image guided radiation therapy (IGRT) uses images, either set-up images obtained just prior to radiation delivery or intra-treatment images, to identify the location of a treatment target (either directly or relative to a known structure within the body) within a treatment room reference frame relative to a treatment planning image reference frame. A physician typically diagnoses a lesion using a 3D image—e.g., MRI, PET, CT or ultrasound—and determines whether radiation is indicated for treatment. The physician then uses the CT image (sometimes fused with an MR image), or obtains a fresh CT image to create a treatment plan, this CT image sometimes referred to as the treatment planning image. The treatment planning image has its own reference frame defined, for example and without limitation, by the person creating the treatment plan. In IGRT challenges arise when attempting to locate within the body a target region (or a structure) that moves, either just prior to, or during the course of radiation treatment, from its location within the body when the treatment planning image was acquired.
Image registration provides the ability to locate a target region within the body by comparing the image content between two or more images. As used herein, “registration” of medical images refers to the determination of a mathematical relationship between corresponding anatomical or other features (e.g. fiducials) appearing in those medical images. Registration can include, but is not limited to, the determination of one or more spatial, alignment or intrafraction transformations that, when applied to one or both of the medical images, would cause an overlay of the corresponding anatomical features. The spatial or alignment or intrafraction transformations can include rigid-body transformations and/or deformable transformations and can, if the medical images are from different coordinate systems or reference frames, account for differences in those coordinate systems or reference frames. For cases in which the medical images are not acquired using the same imaging system and are not acquired at the same time, the registration process can include, but is not limited to, the determination of a first transformation that accounts for differences between the imaging modalities, imaging geometries, and/or frames of reference of the different imaging systems, together with the determination of a second transformation that accounts for underlying anatomical differences in the body part that may have taken place (e.g., positioning differences, overall movement, relative movement between different structures within the body part, overall deformations, localized deformations within the body part, and so forth) between acquisition times. The term alignment transformation refers herein to a transformation between a first coordinate system (for example and not by way of limitation a planning image coordinate system of a patient) and a second coordinate system (a treatment room coordinate system) whereby the alignment transformation determines the location of a target in the second coordinate system relative to the first coordinate system, for example and not by way of limitation at the time of patient setup prior to commencement of the treatment fraction. The term intrafraction transformation refers herein to a transformation between the first coordinate system and the second coordinate system whereby the intrafraction transformation determines the location of the target in the first coordinate system relative to the second coordinate system following commencement of the procedure, for example and not by way of limitation during the treatment fraction.
Knowing where the target is located in the treatment room is important to safely delivering radiation to the target while minimizing delivery to healthy tissue surrounding the target. Accuray's CyberKnife® System tracks targets by comparing two-dimensional (2D) treatment room x-ray images of the patient to 2D digitally reconstructed radiographs (DRRs) derived from three dimensional (3D) pre-treatment imaging data. The pre-treatment imaging data may be computed tomography (CT) data, magnetic resonance imaging (MRI) data, positron emission tomography (PET) data or 3D rotational angiography (3DRA), for example. The treatment room x-ray imaging system of CyberKnife® is stereoscopic, producing images of the patient from two or more different points of view (e.g., orthogonal). Other mechanisms of locating the target are well known to the skilled artisan. For example and not by way of limitation, single image location and tracking is known as described in provisional application 61/408,511, and cone beam CT target location for patient set up on gantry radiation therapy devices is known as described in U.S. patent application Ser. No. 13/156,285.
A DRR is a synthetic x-ray image generated by casting (mathematically projecting) rays through the 3D imaging data, simulating the geometry of the in-treatment x-ray imaging system. The resulting DRR then has the same scale and pose as the treatment room x-ray imaging system, and can be compared with images from the treatment room x-ray imaging system to determine the location of the patient, or the location of the treatment target within the patient relevant to the treatment planning image reference frame. To generate a DRR, the 3D imaging data is divided into voxels (volume elements) and each voxel is assigned an attenuation (loss) value derived from the 3D imaging data. The relative intensity of each pixel in a DRR is then the summation of the voxel losses for each ray projected through the 3D image.
Image registration in general involves computation of similarity values or, equivalently, difference values (e.g., cross correlation, entropy, mutual information, gradient correlation, pattern intensity, gradient difference, image intensity gradients) that are evaluated to determine a spatial transformation between a target's location in a planning room image and a target's location in a treatment room image. In particular, CyberKnife® registers two orthogonal treatment room x-ray images to two corresponding sets of DRRs (one set for each pose of the treatment room x-ray system) to obtain a 2D-3D spatial transformation between the x-ray images and a planning CT.
There is a need to improve on image registration methods to increase the accuracy and computational efficiency in locating a target in one or more images, and thereby more accurately and efficiently determine the spatial transformation between the target's location in a treatment room reference frame relative to a treatment planning image reference frame.